AI that analyzes your session replays to uncover issues and behavior

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Author
Decipher is a next-gen Sentry replacement that helps you uncover, prioritize, and debug production issues faster.Michael Rosenfield
🛠️ 1 tool
Real Product Impact
Decipher determined the real product impact using session replays, code, and error data so you can prioritize and map them to support tickets.
Intelligent Alerting
Decipher's AI distinguishes critical issues from noise, ensuring you only receive alerts that demand your attention. No fussy filters or thresholds required.
Smart Grouping
Decipher automatically clusters related errors, giving you a clear overview of issues affecting your product. The first actually useful error dashboard.
Issue Insights
Decipher reveals patterns and insights across every instance of the same error by analyzing all shared attributes - including requests, logs, and local variables.
AI Debugging
Decipher's AI uses codebase wide understanding and product context to root cause bugs. It can help you get started or even submit a pull request.
Customer Reports, Correlated
Decipher automatically correlates support tickets with relevant errors, bridging the gap between customer reports and monitoring.
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Releases
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May 8, 2024
Michael Rosenfield
Initial release of Decipher.
Pricing
Pricing model
Freemium
Paid options from
$199/month
Billing frequency
Monthly
Prompts & Results
Add your own prompts and outputs to help others understand how to use this AI.
Decipher was manually vetted by our editorial team and was first featured on June 7th 2024.
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35,21224Released 22d agoFree + from $19.99/mo
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836,784636v1.6 released 15d agoFree + from $12/moReducing manual efforts in first-pass during code-review process helps speed up the "final check" before merging PRs
Pros and Cons
Pros
Error cause ascertainment
User impact analysis
Provides bug resolution methodologies
Captures logs for debugging
Captures request bodies for debugging
Captures local variables for debugging
Analysis of session replays
Assessment of runtime data
Source code evaluated
Generates high-signal bug alerts
Uses system-wide runtime data
Compatible with Next.js
Supports Flask framework
Supports FastAPI framework
Supports Express framework
Easy quick-start with few lines of code
Debugs issues automatically
Investigates root cause of bugs
Prioritizes bugs based on analysis
Impactful production monitoring
Includes all needed debugging context
Allows fast debugging
Setup in minutes
Easy SDK installation
Unlocks fast bug fixes
Reproduces and debugs issues
Presents entire stack trace
Provides comprehensive request data
Compiles viable debugging logs
Offers free version
Unlimited errors in paid version
Unlimited codebases in paid version
View 27 more pros
Cons
Limited framework compatibility
No standalone application
Requires adding code lines
Limited team members in Free plan
Free version: limited error notifications
Costly Pro and Business plans
No on-premises version
Limited number of codebases supported
View 3 more cons
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Q&A
What makes Decipher different from other error monitoring platforms?
Differentiating Decipher from other error monitoring platforms is its AI-driven approach to bug detection and resolution. Decipher takes a step further by not only identifying the bugs but also ascertaining the error cause, user impact, and providing methodologies for bug resolution. All this without the need to manually trawl through error logs and code. It also supports session replay, which can help to understand exactly what a user did leading up to an error.
How does Decipher use AI to make bug detection and resolution more efficient?
Decipher uses artificial intelligence (AI) to analyze session replays and runtime data, which helps in efficient bug detection and resolution. The AI system can identify the root cause of each error, generate a user impact analysis and prioritize resolution methodologies based on these findings. It boosts the error monitoring accuracy by examining the source codes and enables teams to swiftly address issues by creating high-signal bug alerts.
What specific information does Decipher capture for debugging issues?
For debugging issues, Decipher captures exhaustive information including logs, request bodies, and local variables. This information is captured automatically once a few lines of code are incorporated into the system.
How does Decipher measure the actual user impact of a bug?
Decipher measures the actual user impact of a bug by analysing individual session replays, runtime data, and source code. This integrated investigation helps in determining the actual user impact of the bug, providing high-signal bug alerts for rapid response and fix.
What platforms and frameworks is Decipher compatible with?
Decipher is notably compatible with Next.js on the frontend. It also supports popular back-end frameworks including Flask, FastAPI, and Express, making it versatile for various system environments.
How easy is it to integrate Decipher into my existing system code?
Integrating Decipher into an existing system code is presented as a straightforward process. With just a few lines of code, Decipher can be embedded to capture all requisite information for debugging issues, making it a quick setup.
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